Complex systems display behavior at a range of scales. Large-scale behaviors can emerge from the correlated or dependent behavior of individual small-scale components. To capture this observation in a rigorous and general way, we introduce a formalism for multiscale information theory. Dependent behavior among system components results in overlapping or shared information. A system’s structure is revealed in the sharing of information across the system’s dependencies, each of which has an associated scale. Counting information according to its scale yields the quantity of scale-weighted information, which is conserved when a system is reorganized. In the interest of flexibility we allow information to be quantified using any function that satisfies two basic axioms. Shannon information and vector space dimension are examples. We discuss two quantitative indices that summarize system structure: an existing index, the complexity profile, and a new index, the marginal utility of information. Using simple examples, we show how these indices capture the multiscale structure of complex systems in a quantitative way.
Multiscale Information Theory and the Marginal Utility of Information
Benjamin Allen, Blake C. Stacey, and Yaneer Bar-Yam
Entropy 2017, 19(6), 273; doi:10.3390/e19060273
Anticorruption initiatives are often put forth as solutions to problems of waste and inefficiency in government programs. It’s easy to see why. So often, somewhere along the chain that links the many participants in public service provision or other government activities, funds may get stolen or misdirected, bribes exchanged for preferential treatment, or genuine consumers of public services supplemented by “ghost” users. As a result, corruption reduces economic growth and leaves citizens disillusioned and distrustful of government. It is tempting to think that more monitoring, stricter sanctions, or positive inducements for suitable behavior will reduce corruption. But every anticorruption or antifraud program elicits a strategic response by those who orchestrated and benefited from wrongdoing in the first place. How can these unintended consequences be anticipated and avoided?
How to fight corruption
Raymond Fisman, Miriam Golden
Science 26 May 2017:
Vol. 356, Issue 6340, pp. 803-804
One hundred and ten Zika virus genomes from ten countries and territories involved in the Zika virus epidemic reveal rapid expansion of the epidemic within Brazil and multiple introductions to other regions.
Zika virus evolution and spread in the Americas
Hayden C. Metsky, et al.
Nature 546, 411–415 (15 June 2017) doi:10.1038/nature22402
The “missing heritability” problem states that genetic variants in Genome-Wide Association Studies (GWAS) cannot completely explain the heritability of complex traits. Traditionally, the heritability of a phenotype is measured through familial studies using twins, siblings and other close relatives, making assumptions on the genetic similarities between them. When this heritability is compared to the one obtained through GWAS for the same traits, a substantial gap between both measurements arise with genome wide studies reporting significantly smaller values. Several mechanisms for this “missing heritability” have been proposed, such as epigenetics, epistasis, and sequencing depth. However, none of them are able to fully account for this gap in heritability. In this paper we provide evidence that suggests that in order for the phenotypic heritability of human traits to be broadly understood and accounted for, the compositional and functional diversity of the human microbiome must be taken into account. This hypothesis is based on several observations: (A) The composition of the human microbiome is associated with many important traits, including obesity, cancer, and neurological disorders. (B) Our microbiome encodes a second genome with nearly a 100 times more genes than the human genome, and this second genome may act as a rich source of genetic variation and phenotypic plasticity. (C) Human genotypes interact with the composition and structure of our microbiome, but cannot by themselves explain microbial variation. (D) Microbial genetic composition can be strongly influenced by the host’s behavior, its environment or by vertical and horizontal transmissions from other hosts. Therefore, genetic similarities assumed in familial studies may cause overestimations of heritability values. We also propose a method that allows the compositional and functional diversity of our microbiome to be incorporated to genome wide association studies.
The Human Microbiome and the Missing Heritability Problem
Santiago Sandoval-Motta, Maximino Aldana, Esperanza Martínez-Romero and Alejandro Frank
Front. Genet., 13 June 2017 | https://doi.org/10.3389/fgene.2017.00080
Information technologies today can inform each of us about the route with the shortest time, but they do not contain incentives to manage travellers such that we all get collective benefits in travel times. To that end we need travel demand estimates and target strategies to reduce the traffic volume from the congested roads during peak hours in a feasible way. During large events, the traffic inconveniences in large cities are unusually high, yet temporary, and the entire population may be more willing to adopt collective recommendations for collective benefits in traffic. In this paper, we integrate, for the first time, big data resources to estimate the impact of events on traffic and propose target strategies for collective good at the urban scale. In the context of the Olympic Games in Rio de Janeiro, we first predict the expected increase in traffic. To that end, we integrate data from mobile phones, Airbnb, Waze and transit information, with game schedules and expected attendance in each venue. Next, we evaluate different route choice scenarios for drivers during the peak hours. Finally, we gather information on the trips that contribute the most to the global congestion which could be redirected from vehicles to transit. Interestingly, we show that (i) following new route alternatives during the event with individual shortest times can save more collective travel time than keeping the routine routes used before the event, uncovering the positive value of information technologies during events; (ii) with only a small proportion of people selected from specific areas switching from driving to public transport, the collective travel time can be reduced to a great extent. Results are presented online for evaluation by the public and policymakers
Collective benefits in traffic during mega events via the use of information technologies
Yanyan Xu, Marta C. González
Published 12 April 2017.DOI: 10.1098/rsif.2016.1041
Royal Society Interface
Volume 14, issue 129